{"id":"W4389335084","doi":"10.1145/3618354","title":"Neural Packing: from Visual Sensing to Reinforcement Learning","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Guelph","funders":"Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Reinforcement learning; Computer science; Container (type theory); Pipeline (software); Artificial intelligence; Packing problems; Benchmark (surveying); Scalability; Encoding (memory); Artificial neural network; Motion planning; Robot; Computer vision; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009298361,0.0001469838,0.0001155963,0.0003660164,0.0002155058,0.00006790978,0.0001065307,0.00008269929,0.00008933154],"category_scores_gemma":[0.00002402179,0.0001655904,0.00007692963,0.001041204,0.00001521164,0.00008910146,0.000004777537,0.0003383298,0.000188334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002664037,"about_ca_system_score_gemma":0.000006876567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003380965,"about_ca_topic_score_gemma":0.00003854468,"domain_scores_codex":[0.9991732,0.00002443549,0.0001877486,0.0001691581,0.0001927439,0.0002526834],"domain_scores_gemma":[0.999483,0.0001252495,0.00001663763,0.000233921,0.00003546095,0.0001057216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006336546,0.000005472186,0.00009030338,0.000009349699,0.0000365474,0.000003655565,0.0006515312,0.9836805,0.0005854503,0.00002935641,0.000192305,0.01470924],"study_design_scores_gemma":[0.0002457683,0.00007815189,0.0005866669,0.00004901119,0.00002297187,0.000001728851,0.0001797511,0.9893703,0.001988927,0.0001993703,0.007023448,0.0002539368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1132136,0.00001438093,0.8821485,0.0007224254,0.0009702183,0.0001939818,0.000008758834,0.002096587,0.0006315372],"genre_scores_gemma":[0.9973216,0.0001220995,0.001884149,0.0002986023,0.00004264783,0.00000719571,0.00004886438,0.00005034668,0.0002244792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.884108,"threshold_uncertainty_score":0.6752582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02469032384299305,"score_gpt":0.2584305126388453,"score_spread":0.2337401887958523,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}